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Sales forecasting for new telecommunications products

Many executives and entrepreneurs are apprehensive about forecasting for entirely new communications technologies. (There is just no historical data to rely upon).

Make a wrong decision here and it could cost you your, profit margin, your job or even your entire business.

This article will reveal a forecasting model that has stood the test of time. To give you the best possible chance of accurately forecasting sales for your new telecommunications products.

Product Lifecycle approach to Telecommunications Sales Forecasting

Given that there is no “historical” sales data to rely upon, how can we scientifically forecast sales? Well, we can go to established theory – The Product Life-cycle.

Introduction Phase: Usually characterized by slow growth. Possibly due to –

Smaller advertising budgets

Poor distribution channels

Poor/no sales training for frontline salespeople

Pent up market demand (or lack thereof)

Growth: The period of fastest uptake by the market.

Maturity: The point of market saturation i.e. when everyone who wants your product has bought it… (The total market for your product).

Decline: As sales drop-off

The above three phases give rise to the famous squiggly “S-shaped” curve we are familiar with from our first year Marketing.

The Product Lifecycle

It is a useful starting framework but how do we get some real numbers out of this “without historical data”?

The Three things you must know about New Tech Telecommunications Sales Forecasting

The Maximum Saturation point: The time in the future when you estimate everyone who wants your product has made a purchase. And the total lifetime number of units to be sold. (I.E. Years and Units).

The Inflection Point of the Product: The time when the product is selling its fastest. After this the sales rate begins to taper off and we enter the second part of the characteristic “S-curve”. The inflection point is the point in time where you expect half the total lifetime sales of your product to be made.

The Delay Factor: Or the amount of time you expect your product to languish in the “Introduction Phase”.

The Product Lifecycle Formula

From the above, you simply plug your variables into the following formula, and it will produce for you the estimated units sold for each month of your Product Life Cycle.

New Product Forecast = S

————————–

1 + B e^-aT

Where:

S = Long run saturation level of the new product

T = Time Index (1,2,3…..)

a = Delay Factor (0-1)

I = Inflection Point ( the point where 1/2 of the saturation point is reached)

B = e^Ia

It produces the signature “S-shaped” Curve of the Product Life Cycle. (As below).

Telecommunications New Product Lifecycle Sales Forecast

So there you have it!

As stressful as sales forecasting for new-tech is, the consequences of doing it in a haphazard fashion are even worse. When you consider what is at risk, a clear and methodical method of sales forecasting is a must.

The Immense Power of Exponential Growth

My father taught me to play Chess. And I am still a terrible player. However, I do remember a wonderful little story about exponential growth he wove around the origins of the game.

Legend has it that an Indian King was presented with a beautifully hand-crafted chess board by a chess-master mathematician. Delighted with the magnificent piece the king asked what the mathematician might like in return. Humbly, the mathematician requested that a grain of rice be put on the 1st square, 2 on the second square, 4 on the third….. doubling at each successive square. The King quickly agreed to his humble request.

Things were going really well (at first) and are summarised in the following table.

Square Number

Grains on that Square

Total Rice on Board

1

1

1

2

2

3

3

4

7

4

8

15

5

16

31

6

32

63

7

64

127

8

128

255

After the first row, the total amounts to 255 grains of rice – barely half a cup full. And some interesting relationships emerge. The total rice on the board is given by

2(Square Number) -1.

For example:

Square Number

2(Square Number) – 1

Total Rice on Board

1

21 – 1

1

4

24 – 1

15

8

28 – 1

255

Then, square 12 =

212 – 1

4095

Based on this how much rice might the King owe at the end of the second row of the Chess Board?

And at the end of the first half of the board? I.E. on the 32nd square?

16

216 – 1

65,535

32

232 – 1

4,294,967,295

So at the half way point (i.e. the 32nd square on the Chess Board), the King owes the mathematician over 4 Billion grains of rice.

You may recall my last blog outlining the relationship between exponential numbers, science and finance. (This has always been a fascination of mine – I mean, interest rates and satellite orbits?? Why?)

We’ll get to that in a minute. Let’s examine natural phenomena – Bacterial growth rates.

Bacteria reproduce by “binary fission”

Let’s assume a single bacterium is put in a jar at 11pm. The bacterium reproduces itself every minute, i.e. the number of bacteria in the jar doubles every minute. The number of bacteria increases in the sequence 1,2,4,8, etc. After 1 hour the jar is completely full….

I ask you at what minute is the jar half full?

That’s right – at 11:59 pm

And at 11:58 pm it is a quarter full.

And at the 11:57 pm it is an eighth full.

And so on, right back to the original bacterium.

Why is this important?

Well, interest rates work that way too! We all know that your money is unlikely to double every minute, but it will double. For example, at 10% your money will double every seven years. And this is easy to calculate…. Just divide 70 by your interest rate:

70/10 = 7 years

The math is based on the natural logarithm of 2 (ie doubling), and 100Ln 2 = 69. Whatever, use your calculator… but trust me its close enough to 70.

Another question…

At 11:58 pm, how many bacteria would have realized that they were running out of room?

And if you retire at age 65 and your money is invested at 10%, how old are you at 11:58pm?

Many of you would know I am a trained accountant. Most would not know that my original training was in science and engineering. It’s that aspect of my life the I would like to write about now.

All of you would however be familiar with the concept of interest rates. A nightly topic on the news, interest rates determine how much spare cash we have after the mortgage payment. And the total mortgage paid is a simple calculation. To save time, I’m going to skip the math… but the formula is:

FV = PV(1+r)^t

Where:

FV = Future value

PV = Present Value

r = Interest Rate

t = time

its the formula for calculating the total amount you pay – and, (just like me), its not very sexy!